Agronomic performance, carbon storage and nitrogen utilisation of long-term organic and conventional stockless arable systems in Mediterranean area

Europ. J. Agronomy 52 (2014) 138–145

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Agronomic performance, carbon storage and nitrogen utilisation of long-term organic and conventional stockless arable systems in Mediterranean area Paola Migliorini a,∗ , Valentina Moschini b , Fabio Tittarelli c , Corrado Ciaccia c , Stefano Benedettelli b , Concetta Vazzana b , Stefano Canali c a

University of Gastronomic Science, Piazza Vittorio Emanuele, 9, 12060 Bra, Cuneo, Italy Department of Plant, Soil and Environmental Science, University of Florence, P. le delle Cascine 18, 50144 Firenze, Italy c Consiglio per la Ricerca e la sperimentazione in Agricoltura, Centro per lo studio delle relazioni tra pianta e suolo, Via della Navicella, 2, 00184 Roma, Italy b

a r t i c l e

i n f o

Article history: Received 29 May 2013 Received in revised form 27 September 2013 Accepted 27 September 2013 Keywords: Organic farming Long term field experiment Nitrogen balance and efficiency Soil carbon sequestration

a b s t r a c t The Montepaldi Long Term Experiment (MOLTE) trial in central Italy has been comparing three agroecosystems with different management: two organic (Old Organic since 1992 and Young Organic since 2001) and one conventional. After sixteen years of comparison, the agronomic performance and environmental sustainability of the three agro-ecosystems were assessed. Crops grain yield, total C inputs and N budget at field level were evaluated. N use efficiency (NUE) at micro-agroecosystem level was determined. Soil samples were collected from the three agroecosystems in order to quantify soil C and N pools. Results showed comparable grain yields in the three agro-ecosystems. The conventional system showed a larger N surplus and a lower crop N use efficiency in comparison with the organic ones. Moreover, the organic systems presented a lower potential risk of N losses with respect to the conventional one. The Young Organic agro-ecosystem was the most effective in terms of long term soil C (13% higher than conventional) and the oldest organic agro-ecosystem was the most effective in terms of soil N storage (9% higher than conventional). The results obtained demonstrated that the application of the organic farming method could increase the environmental sustainability in stockless arable systems under Mediterranean type of climate. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Despite the basic principles of organic farming (OF), which affirm the need for functional interconnections between crop and animal production, organic farming systems in the Mediterranean basin are often stockless (Canali and Speiser, 2005). Accordingly, this is the case for most arable organic cropping systems in Central and Southern Italy. However, stockless farming systems are not present only in Mediterranean regions. Heuwinkel et al. (2005) reported that in Southern Germany organically managed stockless farms ranged between 12% and 42% of the total number of farms. Stinner et al. (2008) found that the number of European farmers who are operating stockless organic crop rotations has been increasing. It is well known that soil fertility and crop nutrition management in organically managed stockless systems are particularly

∗ Corresponding author. Tel.: +39 0172 458573; fax: +39 0172 458500. E-mail address: [email protected] (P. Migliorini). 1161-0301/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.eja.2013.09.017

difficult (Berry et al., 2002; Cormack et al., 2003; Stinner et al., 2008). This is mainly because of the scarcity of organic matter and nutrients (mainly nitrogen) of animal origin to recycle into the systems and the restrictions imposed by the EU Regulation on organic farming (EC Regulation 834/2007) in term of utilisation of organic fertilisers and amendments of off-farm origin (Canali, 2005). Indeed, according to the above mentioned regulation the design of the organic agro-ecosystems should follow agro-ecological sound criteria in order to exploit as much as possible the in-system resources. Moreover, their functioning must comply the basic principles for soil management in organic farming, thus reducing at minimum the use of offfarm allowed N input (those listed in the annex I of the EC Regulation 889/2008). Unfortunately, in current organic operation these criteria and principles are not always considered and, as a consequence, organic systems are often designed according to the input substitution strategy in which the proscribed chemical inputs used in conventional agriculture (i.e. synthetic fertilizers) are replaced by acceptable alternatives (i.e. organic fertilizers of biological origin). This approach leads to the phenomenon

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known as “conventionalization of organic farming” (Darnhofer et al., 2010). In stockless agro-ecosystems, soil organic matter (SOM) conservation is a key aspect of soil management strategies. According to Stockdale et al. (2002), SOM content is the result of the equilibrium, over the long term, between the processes supplying new organic inputs and the rate of mineralisation of the existing soil organic carbon (C) pool. This is particularly relevant under the limitation of Mediterranean conditions where warm temperatures and low and/or uneven distribution of precipitation can lead to high soil mineralisation rates and, consequently, the reduction of SOM (Pant et al., 2004; Montemurro et al., 2008). For this reason data obtained in long-term field experiments (LTE) located in Mediterranean areas are particularly important in studies aimed at evaluating soil C inputs of differently managed agro-ecosystems (i.e. organic and/or integrated systems) and their effect on SOM changes (Köpke, 2006). Similarly, since cycles of carbon and nitrogen (N) are strongly linked, especially in sustainable, low input agro-ecosystems, the evaluation of the potential N storage capacity of soils should be carried out over the long-term time frame, taking into account periods of time longer than a single crop or growing season (Moller, 2009a; Watson et al., 2002). Hence, studies aimed at evaluating the effect of different management on N budget and soil N pool and processes should consider the rotation cycle as minimum time frame. In particular, Fortuna et al. (2008) reported that for a particular tillage or cropping system, the soil N pools may reach a “steady state” condition over a 5–10-year period after the introduction of a relevant change of management. The aim of this study was to assess the long term agronomic and environmental sustainability of differently managed rainfed arable farming systems located in Central Italy (Mediterranean conditions) and characterised by a low amount of off-system C and N inputs of animal origin (stockless farming system). In particular, we wanted to test the hypothesis that in the peculiar Mediterranean conditions, the organically managed systems are able to provide comparable yields respect the conventionally managed ones, present lower potential risk of N leaching and contribute to increase the long term soil N fertility and C storage. For these porpoises, within an existing LTE, a conventionally managed agroecosystem was compared with organically managed systems of two different ages in terms of: (i) grain yield and soil C inputs, (ii) N budget and (iii) soil organic C and N pools size. 2. Materials and methods 2.1. Description of the long term experiment The Montepaldi Long Term Experiment (MOLTE) has been active since 1991 (Bedini et al., 2013; Vazzana et al., 2008; Migliorini and Vazzana, 2007; Vereijken, 1999; Vazzana and Raso, 1998; Vazzana et al., 1997; Vereijken, 1997; Vereijken, 1994) on the farm of the University of Florence (location Montepaldi, San Casciano, Val di Pesa, Long. 11◦ 09 08 E, Lat. 43◦ 40 16 N) covering a slightly sloping surface of about 15 ha at 90 m a.s.l. The MOLTE experiment has a system approach and includes the following three different micro agro-ecosystem managements (AEM): a) “Old Organic” (OldO) of 5.2 ha, divided into 4 fields under organic management (EC reg. 2092/91 and following regulations) since 1992; b) “Integrated/Young Organic” (Int/YngO) with an area of 5.2 ha, divided into 4 fields under EC regulations 2078/92 (integrated farming) from 1992 to 2000 and converted into organic management since 2001;

139

c) “Conventional” (Conv) area of 2.6 ha divided into 2 conventional fields, where farming techniques used were those normally used in the territory of the study area for conventional management. The agroecosystems are surrounded by ecological infrastructures such as natural and artificial hedges in order to avoid as much as possible interaction effects and cross-contaminations among the differently managed fields. A detailed description of the characteristics of the three AEMs of the MOLTE field experiment and of the adopted techniques is reported in Table 1. 2.2. Climate Climatic conditions of the experimental area are typical of the Mediterranean sub-Apennines zone. The annual rainfall is about 770 mm with its maximum in autumn and spring and minimum in the period June–August. The annual mean temperature is 14.1 ◦ C with a maximum which can exceed 30 ◦ C in summer and minimum temperatures in January. Fig. 1 reports the mean values of rainfall, minimum and maximum temperatures which occurred during the studied period (1992–2008). 2.3. Soil characteristics The soil of MOLTE is composed of parent rock material derived from Pliocene sediments (slope zones) and river Pesa fluvial deposit from the Holocene (plane zones),classified as Fluventic Xerochrepts (Lulli et al., 1980). Texture characteristics place the soil between “silty clay loam” and “clay loam” with the common presence of gravel. The initial condition of the soil in 1992 (Table 2) showed a moderate alkaline pH value and medium values of the Cation Exchange Capacity (Ministero delle politiche agricole e forestali, 2000). 2.4. Yield, C input and N budget Crops grain yield data were measured on the entire area of the three fields (one in each micro agroecosystems) where in 2007 maize was cropped (from April to October) and respectively from OldO, Int/YngO and Conv AEM. In order to obtain dry matter yield, values were corrected according to the humidity content determined on sub-samples. Crop residue above ground biomasses (i.e. straw and other above-ground post harvest residues) were estimated according to the harvest indices of the different crops. Harvest indices were obtained from direct field measurements1 and the reliability of the values obtained were verified according to Bolinder et al. (2007). Similarly, the crop root biomass was estimated according to the shoot:root ratio as reported in Bolinder et al., 2007.2 The C and N content in grain yields, crop residues, weeds and green manures were respectively analysed according to Springer and Klee (1954) and by the Kjeldahl’s procedure. N and C content of crop roots were assumed to be the same as the crop residues. C input and N input (or output) per ha of grain yields, crop residues and roots, weeds and green manures were calculated multiplying their own element content (C or N) by the aerial biomass value (dry weight basis) of each component. The amounts (kg ha−1 ) of N and P2 O5 applied to the crops by fertilisers were recorded yearly for every field.

1 HI = 0.28 for sunflower; 0.40 for maize; 0.45 for winter cereals (wheat and barley); 0.50 for field bean. 2 We assumed the following shoot:root ratio = 7.10 for sunflower; 5.60 for maize; 9.46 for wheat and 6.81 for barley; 5.3 for field bean (assumed equal to soybeans); 0.70 for annual clover.

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Table 1 Description of the Montepaldi Long Term Expriment: agroecosystems (AESs) characteristics and main techniques adopted.

Research focus Total area AESs management AESs area

Crop rotation

– – – OldO Int/YngO Conv OldO

Int/YngO

Irrigation Tillage depth Fertiliser typology

Conv – – OldO

Int/YngO

Conv

Weed management

Pest and disease management

OldO Int/YngO Conv OldO Int/YngO Conv

1992–2000

2001–2008

Systems sustainability evaluation + field trials 13 ha OldO/Int/Conv 5.2 ha (4 fields) 5.2 ha (4 fields) 2.6 ha (2 fields) Sunflower − leguminous crop (annual clover or field bean) − winter cereal (wheat or barley) − leguminous crop (annual clover or field bean) Sunflower − winter cereal (wheat or barley) − leguminous crop (annual clover or field bean) − winter cereal (wheat or barley) Sunflower − winter cereal (wheat or barley) No 25–30 cm Mineral and organic (biological origin) 12–13 (N–P2 O5 ) kg ha−1 y−1 winter cereal 18–20 (N–P2 O5 ) kg ha−1 y−1 corn/sunflower Mineral and synthetic 70–60 (N–P2 O5 ) kg ha−1 y−1 winter cereal 65–55 (N–P2 O5 ) kg ha−1 y−1 corn/sunflower Mineral and synthetic 120–70 (N–P2 O5 ) kg ha−1 y−1 winter cereal 95–65 (N–P2 O5 ) kg ha−1 y−1 corn/sunflower Crop rotation, mechanical Crop rotation, chemical Chemical Crop rotation, ecological infrastructures Crop rotation, chemical Chemical

Systems sustainability evaluation + field trials 13 ha OldO/YngO/Conv 5.2 ha (4 fields) 5.2 ha (4 fields) 2.6 ha (2 fields) Green manure + corn − winter cereal (wheat or barley) + red clover − red clover II − winter cereal (wheat or barley) Green manure + corn − winter cereal (wheat or barley) + red clover − red clover II − winter cereal (wheat or barley) Corn − winter cereal (wheat or barley) No 25–30 cm Mineral and organic (biological origin) 12–13 (N–P2 O5 ) kg ha−1 y−1 winter cereal 18–20 (N–P2 O5 ) kg ha−1 y−1 corn/sunflower Mineral and organic (biological origin) 17–20 (N–P2 O5 ) kg ha−1 y−1 winter cereal 14–2 (N–P2 O5 ) kg ha−1 y−1 corn/sunflower Mineral and synthetic 120–70 (N–P2 O5 ) kg ha−1 y−1 winter cereal 95–65 (N–P2 O5 ) kg ha−1 y−1 corn corn/sunflower Crop rotation, mechanical Crop rotation, mechanical Chemical Crop rotation, ecological infrastructures Crop rotation, ecological infrastructures Chemical

Notes: OldO: Old Organic; Int: integrated; Conv: conventional; YngO: Young Organic. Sunflower: Helianthus annuus L.; annual clover: Trifolium alexandrino L. or incarnatum L.; filed bean: Vicia faba L. var. minor; wheat: Triticum aestivum or Triticum durum; barley: Hordeum vulgare; corn: Zea mais; red clover: Trifolium pratense L.

Fig. 1. Monthly rainfall (mm) and minimum and maximum mean air temperature (◦ C) registered during 1992–2008 period at the experimental site.

Table 2 Main soil physico-chemical characteristics of the Montepaldi Long Term Experiment in 1992. Parameter

Units

OldO

Int/YngO

Conv

Gravel Sand Silt Clay Texture pH (H2 O) C.E. C. Total P2 O5 Available P2 O5 a Exchangeable K2 O

% % % %

6.3 20.2 46.3 32.9 Clay loam 8.3 17.6 1.63 22 171

5.1 17.9 49.8 33.3 Silty clay loam 8.3 18.2 1.66 27 143

6.1 21.0 44.6 33.8 Clay loam 8.3 19.4 1.60 29 134

a

Olsen method.

mequiv. 100 g−1 % mg kg−1 mg kg−1

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Table 3 The ANOVA mixed model adopted in the study. (P: 1992–2000; 2001–2008. AEM: OldO; Int/YngO; Conv. C: autumnal/winter; spring/summer). Source of variance

Degree of freedom

Expected value of variance

Period (P)

1

e2 + 2 · 3 · n · P2

AE Management within (nested in) period AEM (P)

4

e2 + 2 · n ·

Crop season (C) Interaction Crop season × period (C × P) Error

2 3

k=1 e2 + 2 · 3 · n · (2−1) 2 e2 + 3 · n· ≤ IntCxp e2

1 1 40

The N budget was evaluated following the criteria proposed by Watson et al. (2002) for the calculation of the surface input/output balance. According to Moller (2009a), the atmospheric N deposition, asymbiotic N2 fixation and gaseous losses via denitrification (N2 and N2 O), were not included in the N budget due to the difficulties in assessing reliable amounts of these inputs and losses. Moreover, all the N contained in the above and below soil biomass of legume green manure was accounted for N derived from the atmosphere via biological N fixation (BNF) and integrally included in the input. Conversely, according to Watson et al. (2002) who reported that almost all the N fixed via BNF by grain legume crops is exported from the system with the grain yield, the contribution of these crops to the input was not taken into account. Outcome uncertainty related to the simplified proposed approach was discussed in depth by Oenema et al. (2003). However, since in our experiment a direct comparison among the AEM was carried out, thus reducing spatial and temporal variability, biases and errors embedded in the N budget methodology had a limited impact on interpretation of the results. Nitrogen use efficiency (NUE) at microagroecosystem level was evaluated by the N output to N input ratio (output per unit of input) and the N surplus to N output ratio (surplus per unit of output), which can both be derived from the N budget estimation (Doumburg et al., 2000). 2.5. Soil sampling and analysis Soil samples were collected in October 2007 from three fields (one form each agroecosystems) of the MOLTE facility where maize was previously cropped and respectively from OldO, Int/YngO and Conv. For each of the sampled fields, four samples were collected at 0–25 cm soil depth. To avoid any edge effect, a 5.0 m step down each side and a 20.0 m strip at both end of the field were not sampled. The four sub-samples were collected along a transect, running the length of the field. Each sub-sample was obtained with 12 boreholes taken at regular intervals (about 10 m) and were joined on field just after the collection. The four sub-samples obtained were then airdried, crushed, passed through a 2-mm sieve (USDA-NRCS, 1996) and stored for subsequent analyses. All the laboratory tests were carried out in three replicates in order to control intra-laboratory variability. 2.6. Determination of soil C pools Total soil organic carbon (Corg ) was determined by wet mineralisation with 2 N K2 Cr2 O7 and 96% H2 SO4 solutions at 160 ◦ C for 10 min according to Springer and Klee (1954). The content of organic carbon was calculated by back-titration with a solution of 0.2 N FeSO4 . In order to measure humic and fulvic acid C, extractable organic carbon was extracted from 5 g of soil by adding 100 mL of 0.1 N NaOH/0.1 N Na4 P2 O7 solution at 65 ◦ C for 48 h, under N2 atmosphere. Aliquots of each NaOH/Na4 P2 O7 extract were stored under N2 at 4 ◦ C. Humic acids (HA) were precipitated from 25 mL of the extract by adding a solution of 50% H2 SO4 , drop by drop until pH < 2. After centrifugation at 2500 rpm, the non humified fraction

i=1

˛2 j=1 ij

2·(3−1)  2 2 

k

was eliminated from the solution containing fulvic acids (FA) by purification on a polyvinylpyrrolidone column (PVP) (Ciavatta et al., 1990). Humic and fulvic acid carbon (CHA+FA ) determination was performed on 10 mL of 0.5 N NaOH solutions, following the same procedure reported above for Corg determination (Ciavatta and Govi, 1993). Humification parameters, such as the humification rate (HR) and the degree of humification (DH), were calculated as follows (Ciavatta et al., 1990):

 HR(%) =

DH(%) =

CHA+FA Corg

C

HA+FA

Cextr.

 

× 100

(1)

× 100

(2)

Soil C mineralisation was studied by measuring CO2 –C production in closed jars (Isermeyer, 1952). Each soil sample (25 g, oven dry-weight equivalent) was rewetted to their −33 kPa water tension and incubated at 30 ◦ C. The CO2 evolution was determined by back titration of NaOH absorbed CO2 at the 1st (C1 ), 2nd, 4th, 7th, 10th, 14th, 17th and 21st day of the incubation period. The kinetic study of the organic C dynamics was performed by fitting the cumulative CO2 –C vs. time according to a first order exponential function [Ct = C0 (1 − e−kt )]. This allowed us to calculate the potentially mineralisable C pool (PMC) for each soil sample. Carbon of soil microbial biomass (Cmic ) was measured by the chloroform fumigation-extraction method (Vance et al., 1987) on air-dried soil samples conditioned by a 21-day incubation in open glass jars at −33 kPa water tension and 30 ◦ C. Soil samples were incubated for restoring the microbial activity of air-dried soils. The metabolic quotient q(CO2 ), defined as specific soil respiration of the microbial biomass, was calculated as the ratio of basal respiration values (after the 21st day) and microbial biomass C according to Anderson and Domsch (1985).

2.7. Determination of soil N pools Total soil nitrogen (Ntot ) was determined by Kjeldahl’s procedure (Bremner and Mulvaney, 1982). Potentially mineralisable N (NPM) was estimated by calculating the NH4 + -N (mg kg−1 ) accumulated after 7 days of anaerobic incubation at 40 ◦ C, according to Sahrawat and Ponnamperuma (1978) and slightly modified by Canali et al. (2004). Sixteen grams of air-dried and sieved (<2 mm) soil, were placed in 50 mL test tubes containing 40 mL of distilled water; the tubes were then sealed, incubated at 40 ◦ C for 8 days, and shaken for a few seconds each day, in order to mix the water–soil suspension. After incubation, soil was extracted with 80 mL of 2 N KCl, and 40 mL of 4 N KCl were added to the suspension in order to reach a soil:solution ratio of 1:5. Samples were shaken for 1 h and then filtered through Whatman’s No. 40 filter paper. Anaerobiosis was controlled by determining the NO3 -N concentrations at the end of incubation. Only negligible traces of the oxidised form of N were observed. Determinations were repeated three times and

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Table 4 Mean crop yield (D.M. t ha−1 ) of the three cropping systems of the Montepaldi Long Term Experiment (MOLTE). Values in row followed by different letters are significantly different (*P ≤ 0.05; **P ≤ 0.01; n.s., not significant) as determined by the Tukey’s Multiple Range Test (TMRT). Period

AEManagement (period)

1992–2000

2001–2008

2.77 a *

2.19 b

1992–2000

Crop season × period

Crop season 2001–2008

Conv

Int

OldO

Conv

YngO

OldO

3.15 n.s.

2.80

2.24

2.30

2.21

2.06

Winter

Spring

2.76 A **

2.01 B

1992–2000

2001–2008

Winter

Spring

Winter

Spring

3.56 n.s.

2.27

2.32

1.80

Table 5 N system budget (estimated values, in kg ha−1 ) and N indices of the corps in the three cropping systems of the Montepaldi Long Term Experiment (MOLTE). Values in row followed by different letters are significantly different (*P ≤ 0.05; **P ≤ 0.01; n.s., not significant) as determined by the Tukey’s Multiple Range Test (TMRT). Sign

N input N output N surplus (deficit) N output/N input N surplus/N output

** n.s. ** n.s. **

1992–2000

2001–2008

Conv

Int

OldO

Conv

YngO

OldO

127.6 A 54.1 73.5 A 0.41 1.83 A

49.1 BC 56.1 −7.0 B 0.81 0.23 B

7.0 C 44.6 −37.6 B 0.45 −0.63 B

76.2 BC 39.5 36.7 AB 0.61 1.68 A

31.2 BC 46.6 −15.4 B 0.79 0.28 AB

31.3 BC 37.2 −5.9 B 0.93 −0.13 B

the difference between the N-NH4 + after 7 days and that at 0 days represents the potentially mineralisable N (NPM). 2.8. Statistical analysis Data for the dependent variables Yield, TotC, TotN, Nout, Noutput/Ninput and NSurplus/Noutput were subjected to univariate analysis of variances (ANOVA) utilising the SPSS 16.0 statistical software package. The statistical design is a split plot where the main factor is the period (1: 1992–2000; 2: 2001–2008) and the second factor is the agroecosystem management (treatments). This is an effect of the system approach where the factors cannot be replicate in single plots and cannot be completely randomised because of the technical difficulty to have a representative system. The adopted mixed model is reported in Table 3. The period was considered as random effect factor (P); while the three agroecosystem managements (AEM) and the two crop seasons (C) were considered as fixed effect factors. The agroecosystem management factor was considered as nested factor inside the period, because of the different combination within period. There are a total of 48 observations as there are 2 periods × 3 agroecosystems management (one field for each AEM) × 8 years in each period (considered as replications), and inside of each year there are two crop season not always present every year. The multiple mean comparison was carried out according to the Tukey Multiple Range Test (TMRT) at P ≤ 0.05 and P ≤ 0.01 probability level. Also data for the soil C and N pools were subjected to univariate analysis of variance (ANOVA) utilising the SPSS 16.0 statistical software package. Mean comparison for these parameters was carried out according to the Duncan Multiple Range Test (DMRT) at P ≤ 0.05 probability level. 3. Results Mean grain yield of the crops of the three AEMs of MOLTE (t ha−1 , dry weight basis) for the 1992–2000 and the 2001–2008 periods are reported in Table 4. The mean crop grain yield was 21% statistically higher in the first than the second period. The yield of the winter crops (soft wheat, hard wheat, barley, field bean, barley + clover, annual clover, clover II, green manure + corn) is significantly higher (29%) than that of spring crops (spring barley, sunflower, corn, spring clover). As reported above, because of the different rotation within the two periods, the effect of agroecosystem management factor on

Table 6 Main soil N pools and C/N ratio of the Montepaldi Long Term Experiment. Parameter

Conv

Int/YngO

OldO

Total N (mg kg−1 ) NPM (mg N-NH4 + kg−1 ) C/N

1116 b 7.07 c 8.82 b

1144 b 17.23 b 9.39 a

1219 a 23.24 a 8.55 b

Notes: NPM: potentially mineralisable N; in the same row, letters indicate mean values significantly different according to DMRT at the P ≤ 0.05 probability level.

yield was considered as nested factor inside the period. Results obtained showed that no significant differences in grain yield were observed among the three different micro-agroecosystems either within the first (1992–2000) or within the second (2001–2008) period (Table 4). In Table 5 the N mean crop budget of the three AEMs during the two period (1992–2000 and 2001–2008) is reported. The N surplus value of the Conv system in the 2001–2008 period was 40% lower than the 1992–2000 period probably because of the lower amount of N synthetic fertiliser used after 2000 (Table 1). As far as the Int/YngO system is concerned, the N deficit was moderate while it was managed according to the integrated approach (1992–2000) and, as a consequence of the reduction of N applied with fertilisers, doubled after the conversion to organic (2001–2008). On the other hand, the N deficit value of OldO in 2001–2008 period was 84% lower than that of the 1992–2000 period. This result was due to the larger use of green manure and off-farm origin organic fertilisers and amendments in the OldO system in the 2001–2008 period. The high N surplus value of the Conv treatment was reflected in the low utilisation efficiency of this nutrient by crops as confirmed by the low N output/N input ratio. Conversely, both the other two studied systems showed a higher N output/N input ratio indicating that, in these two systems, N was utilised more efficiently than in the Conv system. Results about total soil N, potentially mineralisable N and C/N ratio of the three AEMs are reported in Table 6. The overall average value of C input was 1.58 t ha−1 crop−1 and no significant differences were observed among all the tested factors (management, period and crop typology) for this parameter. Fig. 2 represents the relative amount of the C input (%) divided by the different typology of sources (i.e. crop residues and roots, weeds, green manures, organic fertilizers and amendments) received by the three AEMs of MOLTE. Table 7 reports the main C pools measured in the MOLTE AEMs soil. The highest value of Corg was shown by the Int/YngO system.

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Fig. 2. Relative amount (%) of C input of the three AEMs of MOLTE divided by source type.

Table 7 Main soil C pools measured in the Montepaldi Long Term Experiment. Parameter

Conv

Int/YngO

OldO

Corg (mg kg−1 ) CHA+FA (mg kg−1 ) HR (%) DH (%) PMC (mg C-CO2 kg−1 ) Cmic (mg kg−1 ) q(CO2 ) (mg C-CO2 mg Cmic −1 h−1 ) × 102

9834 b 4766 b 48.52 65.78 321.7 b 130.4 0.24

11,155 a 6073 a 54.42 60.69 387.5 a 107.1 0.44

10,757 a 5129 ab 47.66 69.63 347.6 b 105.7 0.44

Notes: Corg : total organic C; CHA + FA : humic and fulvic C; HR: humification rate; DH: degree of humification; PMC: potentially mineralisable C; Cmic : C of soil microbial biomass; q(CO2 ): metabolic quotient; in the same row, letters indicate mean values significantly different according to DMRT at the P ≤ 0.05 probability level.

The higher amount of humified C (CHA+FA ) was probably due the higher amount of Corg. In fact, both the humification rate (HR) and the degree of humification (DH), which indicate the amount of humified material per unit of Corg, were not statistically different among the three systems. The potentially mineralisable C pool showed the highest value in the Int/YngO system and the lowest in the Conv (significant difference) and these results were probably attributable to the differences in Corg content. The OldO system showed intermediate values, not statistically different from the Conv system. No statistically significant differences were observed for the size of microbial populations (Cmic ) and the metabolic quotient (qCO2 ) among the three systems (Table 6).

4. Discussion The difference mean grain yield in the two study periods is determined by the substitution of sunflower, cultivated in the period 1992–2000 with corn, introduced in the 2001–2008 period (Table 1), which yielded less than sunflower. Moreover during the second period less external input were used in the systems, according to an agroecological strategy. The higher mean yield of the winter crops is probably attributable to the fact that in rainfed agro-ecosystems, crops cultivated during the wet season (winter) perform better that those grown during the dry (spring–summer) season, in which water is a limiting factor. Similar results were observed by other Authors in similar environment and conditions. In particular, in their longterm study in rain-fed cereal systems in the hilly area of Marche region – Central Italy, De Sanctis et al. (2012) reported an average grain yield of 3.3 and 1.9 t ha−1 for winter wheat and spring maize, respectively.

The lack of statistical difference in the yield among the three agro-ecosystems is not in accordance with the results reported by Acs (2007) who compared conventional and organic arable farming systems in the Netherlands. Also Korsaeth (2008) in his study, in which six farming systems were compared in a long-term experiment facility located in southeast Norway, found that organic arable cropping systems gave significantly lower grain yields than conventional ones and attributed these results to the sub-optimal plant nutrition and the lack of plant protection in the organic system. Even if weed density and species could determine grain yield reduction in organic arable systems, Olesen et al. (2007, 2009) reported that, in both spring and winter cereals, yield effects of N supply were more predictable and less variable than the effect of weed infestation. Moller (2009b) reported that grain yields of non-legumes in arable cropping in organic farming systems were limited by N shortage. However, this seemed not to be the case of the MOLTE. In fact, the Conv systems, where both the spring cereal (corn) and the winter cereal (wheat) included in the two year conventional rotation were fertilised by synthetic N fertilisers, performed similarly to the OldO and Int/YngO systems, where legume crops were introduced in the rotation in order to supply N aimed at matching the N needs of the crops via biological fixation (NBF). Similarly, the other main nutrients (namely, P and K) were available in adequate amount in all the systems, as the values for available P and exchangeable K measured in the MOLTE soil were largely above the target threshold set up according to the criteria for fertility evaluation of silty clay loam soils in Central Italy. Thus not being limiting factors did not affect yield of the three compared management systems (Ministero delle politiche agricole e forestali, 2000, Table 2). The N surplus (deficit) value as well as the N surplus/N output ratio give information about the potential risk of N losses from the system (Lord et al., 2002; Jansons et al., 2003). Thus, even if these parameters were considered to be weak indicators for the risk of nitrate leaching in comparison to the direct measurements of losses and/or of soil mineral content measured at the beginning of the wet season, they allowed us to evaluate the potential impact on the environment and water quality of the different agro ecosystems studied (Moller, 2009a). In fact, the establishment of nutrient balance at field and farm level has often been advocated as a method to quantify apparent nutrient use efficiencies and take informed decisions about the potential of management measures to reduce nutrient losses (Watson et al., 2002; Öborn et al., 2003; Oenema et al., 2003). According to Langeveld et al. (2007), the use of Nitrogen Surplus to compare operational management of different groups of farms can only be valid if such groups are homogeneous with respect to activities and internal N flows at field level. Accordingly,

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referring N surplus to the N output (i.e. N surplus/N output) enables us to make a direct comparison among the MOLTE AEMs. In our experiment, the Conv system presented the higher potential risk of N losses (largely positive N surplus and high N surplus/N output ratio value, Table 5) with respect to the two other systems (Kirkmann and Bergstrom, 2001). However, since we did not carry out direct measurements on either soil mineral N content or on N losses through the atmosphere, we were not able to draw any conclusion about the destination of the N surplus and further studies in the same environment and in similar cropping systems are needed. Total soil N content (Table 6) was significantly higher in the OldO system than the Conv one. The Int/YngO system assumed intermediate values, even if it did not show significant difference from the Conv system. However, the lower value of soil total N showed by the Conv system despite it having a large N surplus was a further confirmation of the occurrence of N losses from this system. The potentially mineralisable N behaved similarly, ranking OldO > Int/YngO > Conv (significant differences among all three treatments). These differences are probably due to the different management and characteristics of the soil N input of the systems. In fact, while the N input in the Conv system was represented by synthetic N fertilisers, in the OldO they were organic fertilisers and green manure, thus more efficient in increasing the organic soil N pool, which contributed to the NPM soil pool formation. Thus, the application of these inputs over time contributed to the increase of the long term soil N fertility status (Moller, 2009a; Watson et al., 2002; Fortuna et al., 2008) and could contribute to explain why on the long term the organic treatment yielded similarly to the Conv one despite the large difference in the N input. The intermediate values showed by the Int/YngO treatment could be explained considering that this system was managed according to the integrated approach (using synthetic N fertilisers) until 2000 and then converted to organic management, substituting the synthetic N input with the organic ones. As far as C input results is concerned, our findings were not in accordance with Leifeld (2009) who found that C input of cropping systems was linked to the total grain yield. In fact, we observed significant differences among periods and crop typology factors for the grain yield while the C input value did not show any significant difference. Moreover, in the MOLTE there was not a positive relationship between C input and soil organic C content. This finding was not in accordance with what has been reported by many authors (Larson et al., 1972; Havlin et al., 1990; Rasmussen and Collins, 1991; Paustian et al., 1992; Buyanovsky and Wagner, 1998; Lugato et al., 2006). Despite that, according to Drinkwater et al. (1998), our results could be explained taking into account not only the quantity but also the different quality of C input received by the systems (crop and root residues for the conventional vs. a wider range of materials for the two organic systems, Fig. 2). The lack of significant differences in potentially mineralisable C pool, size of microbial populations (Cmic ) and the metabolic quotient (qCO2 ) among the three agro-ecosystems might indicate that in Mediterranean conditions, despite the different quality of C input and the consequently different amount of available C substrates in the organic systems, soil microorganisms followed the same metabolic pattern in all systems. These findings are in contrast with results obtained by Mäder et al. (2002) and Franca et al. (2007) who, however, carried out their studies in areas not characterised by a Mediterranean type of climate. Thus, the comprehensive evaluation of all the soil C pools and parameters measured suggest a stronger capacity for carbon sequestration in the organic systems compared to the conventional one. These findings are in accordance with what has been reported by other authors (Drinkwater et al., 1998; Mader et al., 2003; Pimentel et al., 2005). In particular, the OldO system, in

which the organic farming method was applied earlier than in the Int/YngO systems shown the greatest C sequestration capability. This evidence was further confirmed by the values of the soil PMC to soil Corg ratio, which was lower in the OldO system with respect to the Int/YngO and the Conv (data not showed). 5. Conclusion The results obtained in this long term study demonstrated that both the organic farming systems produced comparable grain yield respect to the conventional one. On the other hand, the conventional system showed a large N surplus and a lower crop N use efficiency with respect to the organic systems. Moreover, both the YngO and the OldO systems presented a lower potential risk of N losses with respect to the conventional one. Furthermore, the OldO one was the most efficient in terms of long-term soil C and N storage. These findings, which are equivalent to those obtained by other Authors in similar studies carried out in areas characterised by different climatic conditions (i.e. Northern Europe and continental USA), suggested that the application of the organic farming method could increase, over the long-term, the environmental sustainability also in stockless arable systems under Mediterranean type of climate. Accordingly, the acknowledgement of the positive role of organic farming could be helpful to the policy makers to set up specific agro-environmental measures for the Mediterranean regions. Acknowledgments The authors wish to thank Giovanna Casella and Roberto Vivoli for their help in sampling field data at MOLTE and Olimpia Masetti and Alberto Alianello for their help in soil chemical and biochemical analysis. This study was carried out in the framework of the SIMBIOVEG (www.simbioveg.org) research project, funded by the Italian Ministry of University and Scientific Research. References Acs, S., 2007. Comparison of conventional and Organic arable farming systems in the Netherlands by means of bio-economic modelling. Biol. Agric. Hortic. 24 (4), 341–361. Anderson, T.H., Domsch, K.H., 1985. Ratios of microbial biomass carbon to total organic-C in arable soils. Soil Biol. Biochem. 21, 471–479. Bedini, S., Avio, L., Sbrana, C., Turrini, A., Migliorini, P., Vazzana, P., Giovannetti, M., 2013. Mycorrhizal activity and diversity in a long-term organic Mediterranean agroecosystem. Biol. Fertil. Soils 49, 781–790. Berry, P.M., Sylvester-Bradley, R., Phillips, L., Hatch, D.J., Cuttle, S.P., Rayns, F.W., 2002. Is the productivity of organic farms restricted by the supply of available nitrogen? Soil Use Manag. 18, 248–255. Bolinder, M.A., Janzen, H.H., Gregorich, E.G., Angels, D.A., Van den Bygaart, A.J., 2007. An approach for estimating net primary productivity and annual carbon inputs to soil for common agricultural crops in Canada. Agric. Ecosyst. Environ. 118, 29–42. Bremner, J.M., Mulvaney, C.S., 1982. Nitrogen total. In: Page, A.L. (Ed.), Methods of Soil Analysis. Part 2. , 2nd ed. Agron. Monogr. 9. ASA and SSSA, Madison, WI, pp. 595–624. Buyanovsky, G.A., Wagner, G.H., 1998. Changing role of cultivated land in the global carbon cycle. Biol. Fertil. Soils 27, 242–245. Canali, S., 2005. Fertilisers and soil conditioners in organic farming in Italy. In: Canali, S., Speiser, B. (Eds.), Current Evaluation Procedures for Fertilisers and Soil Conditioners Used in Organic Farming. Proceedings of a Workshop of the Organic Input Evaluation Project (ORGIN), Emerson College (UK), 29–30 April 2004. Research Institute for Organic Farming (FiBL), Frick, CH, pp. 37–44, ISBN: 3-906081-65-6. Canali, S., Speiser, B.,2005. Current evaluation procedures for fertilisers and soil conditioners used in organic farming. In: Proceedings of a Workshop of the Organic Input Evaluation Project (ORGIN), Emerson College (UK) 29–30 April 2004. Research Institute for Organic Farming (FiBL), Frick, CH, p. 100, ISBN: 3-906081-65-6. Canali, S., Trinchera, A., Intrigliolo, F., Pompili, L., Nisini, L., Mocali, S., Torrisi, B., 2004. Effect of long term addition of composts and poultry manure on soil quality of citrus orchards in Southern Italy. Biol. Fertil. Soils 40, 206–210.

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